1. Field
The present invention relates to a system and method of detecting objects in scene point clouds.
2. Background
Object detection is one of the most basic tasks in computer vision. Numerous techniques focused on detection of humans, human faces, cars, ships, daily life objects, etc. Until recently, however, most techniques were only limited to two-dimensional (2D) image data. With the development of sensor technology in recent years, three-dimensional (3D) point clouds of real scenes have been increasingly popular and precise. However, very few methods that directly detect objects from 3D point clouds are presently available.
Conventional point cloud processing can be divided into several categories based on their focus: segmentation, classification, matching, modeling, registration and detection. Object detection in the scene point cloud is a systematic work that typically requires multiple techniques in different aspects. Various point cloud processing have been applied to various forms of data such as detection of vehicles, poles and other outdoor objects in urban scenes, detection/classification of chairs, tables and other indoor objects in the office scenes, etc. None of the conventional point cloud processing has been implemented in industrial scene point clouds, which may include complex object shapes and a complex arrangement of the objects in a scene.